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Atmospheric Correction of Multi-Spectral Littoral Images Using a PHOTONS/AERONET-Based Regional Aerosol Model

机译:使用基于光子/航空网的区域气溶胶模型对多光谱滨海图像进行大气校正

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Spatial resolution is the main instrumental requirement for the multi-spectral optical space missions that address the scientific issues of marine coastal systems. This spatial resolution should be at least decametric. Aquatic color data processing associated with these environments requires specific atmospheric corrections (AC) suitable for the spectral characteristics of high spatial resolution sensors (HRS) as well as the high range of atmospheric and marine optical properties. The objective of the present study is to develop and demonstrate the potential of a ground-based AC approach adaptable to any HRS for regional monitoring and security of littoral systems. The in Situ-based Atmospheric CORrection (SACOR) algorithm is based on simulations provided by a Successive Order of Scattering code (SOS), which is constrained by a simple regional aerosol particle model (RAM). This RAM is defined from the mixture of a standard tropospheric and maritime aerosol type. The RAM is derived from the following two processes. The first process involved the analysis of a 6-year data set composed of aerosol optical and microphysical properties acquired through the ground-based PHOTONS/AERONET network located at Arcachon (France). The second process was related to aerosol climatology using the NOAA hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model. Results show that aerosols have a bimodal particle size distribution regardless of the season and are mainly represented by a mixed coastal continental type. Furthermore, the results indicate that aerosols originate from both the Atlantic Ocean (53.6%) and Continental Europe (46.4%). Based on these results, absorbing biomass burning, urban-industrial and desert dust particles have not been considered although they represent on average 19% of the occurrences. This represents the main current limitation of the RAM. An assessment of the performances of SACOR is then performed by inter-comparing the water-leaving reflectance ( ρ w ) retrievals with three different AC methods (ACOLITE, MACCS and 6SV using three different standard aerosol types) using match-ups (N = 8) composed of Landsat-8/Operational Land Imager (OLI) scenes and field radiometric measurements. Results indicate consistency with the SWIR-based ACOLITE method, which shows the best performance, except in the green channel where SACOR matches well with the in-situ data (relative error of 7%). In conclusion, the study demonstrates the high potential of the SACOR approach for the retrieval of ρ w . In the future, the method could be improved by using an adaptive aerosol model, which may select the most relevant local aerosol model following the origin of the atmospheric air mass, and could be applied to the latest HRS (Sentinel-2/MSI, SPOT6-7, Pleiades 1A-1B).
机译:空间分辨率是解决海洋沿海系统科学问题的多光谱光学太空任务的主要仪器要求。该空间分辨率应至少为十进制的。与这些环境相关的水生颜色数据处理需要特定的大气校正(AC),该校正适用于高空间分辨率传感器(HRS)的光谱特性以及大气和海洋光学特性的大范围范围。本研究的目的是开发和展示适用于任何HRS的地面交流方法的潜力,以用于区域监测和沿海系统的安全性。基于原位的大气校正(SACOR)算法基于由连续散射码(SOS)提供的模拟,该模拟受简单的区域气溶胶粒子模型(RAM)约束。该RAM是由标准对流层和海洋气溶胶类型的混合物定义的。 RAM从以下两个过程派生。第一个过程涉及对6年数据集的分析,该数据集由通过位于法国阿尔卡雄的地面PHOTONS / AERONET网络获取的气溶胶光学和微物理特性组成。第二个过程与使用NOAA混合单粒子拉格朗日综合轨迹(HYSPLIT)模型的气溶胶气候学有关。结果表明,无论季节如何,气溶胶都具有双峰粒径分布,并且主要表现为混合的沿海大陆型。此外,结果表明,气溶胶来自大西洋(53.6%)和欧洲大陆(46.4%)。根据这些结果,尽管吸收燃烧的生物质,城市工业和沙漠尘埃颗粒平均占发生率的19%,但尚未考虑。这代表了RAM的主要电流限制。然后,通过使用匹配(N = 8)将三种不同的AC方法(ACOLITE,MACCS和6SV,使用三种不同的标准气溶胶类型)相互比较留水反射率(ρw),对SACOR的性能进行评估。 )由Landsat-8 / Operational Land Imager(OLI)场景和野外辐射测量组成。结果表明与基于SWIR的ACOLITE方法保持一致,该方法显示出最佳性能,但绿色通道中SACOR与原位数据匹配良好(相对误差为7%)。总之,该研究证明了SACOR方法在ρw检索中的巨大潜力。将来,可以通过使用自适应气溶胶模型来改进该方法,该模型可以根据大气质量的起源选择最相关的局部气溶胶模型,并且可以应用于最新的HRS(Sentinel-2 / MSI,SPOT6 -7,P 1A-1B)。

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